Right, user-confirmed "translation" is the responsible way to put LLMs into general computing flows, as opposed to stuffing them in everything willy-nilly like informational asbestos mad-lib machines powered by hope an investor speculation.

Another example might be taking a layperson's description "articles about Foo but not about Bar published in the last two months" and using to suggest (formal, deterministic) search-parameters which the can view and hopefully understand before approving.

Granted, that becomes way trickier if the translated suggestion can be "evil" somehow, such as proposing SQL and the dataset has been poisoned so that it "recommends" something that destroys data or changes a password hash... But even that isn't nearly the same degree of malpractice as making it YOLO everything.